Machine Learning with Python

(6 customer reviews)

$81.14

This course teaches machine learning with Python, focusing on key concepts like supervised and unsupervised learning, classification, regression, and clustering algorithms. You’ll work with libraries like Scikit-learn and TensorFlow to build predictive models, learning to train, evaluate, and optimize them using real-world datasets. The course covers essential techniques like cross-validation and hyperparameter tuning, helping you improve model accuracy. Ideal for Python users looking to expand into AI, this course equips you with the skills to build and apply machine learning models in a variety of contexts.

Description

This machine learning course is designed for those with a basic understanding of Python who want to dive into the world of artificial intelligence and predictive modeling. You’ll begin by learning the key concepts in machine learning, including supervised and unsupervised learning, and how these approaches are used to train models. Through practical, hands-on projects, you’ll explore different types of algorithms, such as linear regression, decision trees, support vector machines, and clustering algorithms like k-means. The course uses popular Python libraries such as Scikit-learn, TensorFlow, and Keras to implement these models, allowing you to apply machine learning techniques to real-world datasets. You’ll also learn about important concepts like model evaluation, cross-validation, and hyperparameter tuning to improve your models’ accuracy and performance. By the end of the course, you’ll have experience building and optimizing machine learning models, enabling you to predict outcomes, classify data, and make data-driven decisions. Whether you’re interested in pursuing a career in AI or simply want to expand your programming skill set, this course provides a deep dive into the exciting and fast-growing field of machine learning.